{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "ReservoirPressureProfile.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyPuW8+ag3JK8mexriZEA+R0",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Divyanshu-ISM/Oil-and-Gas-data-analysis/blob/master/ReservoirPressureProfile.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DT5olCJEJZcH",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#How pressure profile changes when you change different parameters in Darcy's LAW\n",
        "#Darcy's law - q = kh(DP)/(141.2uBln(re/rw))\n",
        "#- DP = (141.2quB/kh).ln(re/rw)\n",
        "# P = Pwf + DP(r)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V6gjbPPdJxxk",
        "colab_type": "code",
        "outputId": "9dc7180f-0f37-482e-9a9f-03b9229ef741",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "\n",
        "# #TIPS to use the TOOL-\n",
        "# 1. Use only 2 cases to compare, which will give you a clearer picture. \n",
        "# 2. enter the same properties in both cases, except for which you want to see the effect of. \n",
        "# EXAMPLE- I wanted to see the effect of viscocity so i have changed nothing but viscocity. \n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([3, 2, 1])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W2pi7H90LuU5",
        "colab_type": "code",
        "outputId": "d745539b-9048-4761-a6fa-3eca9bdb1919",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 800
        }
      },
      "source": [
        "ans = 'yes'\n",
        "p = []\n",
        "while ans.lower() == 'yes':\n",
        "  r = np.linspace(1,3000,num=50)\n",
        "  print(\"\\n Enter the Properties\")\n",
        "  q = int(input(\"\\nFlow rate Q(STB/D)- \"))\n",
        "  u = int(input(\"\\nOil viscocity(cp)- \"))\n",
        "  B = 1.2 #bbl/stb\n",
        "  k = int(input(\"\\nPermeability(mD)- \"))\n",
        "  h = int(input(\"\\nReservoir thickness(ft)- \"))\n",
        "  Pe = 3000 #psi\n",
        "  rw = 0.5 #ft\n",
        "  DP = (141.2*q*u*B/(k*h))*(np.log(3000/r))\n",
        "  P = Pe - DP\n",
        "  p.append(P)\n",
        "  ans = input('\\n Want to try again? (yes/no)-')\n",
        "\n",
        "\n",
        "plt.figure(figsize=(10,6))\n",
        "for i in range(len(p)):\n",
        "  \n",
        "  plt.plot(r,p[i])\n",
        "  plt.xlim(1,3000)\n",
        "  plt.ylim(0,5000)\n",
        "  plt.xlabel('distance from the well,r(ft)--->')\n",
        "  plt.ylabel('Pressure P(psi)')\n",
        "  plt.legend(['case1','case2'])\n",
        " \n",
        "\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            " Enter the Properties\n",
            "\n",
            "Flow rate Q(STB/D)- 200\n",
            "\n",
            "Oil viscocity(cp)- 10\n",
            "\n",
            "Permeability(mD)- 150\n",
            "\n",
            "Reservoir thickness(ft)- 30\n",
            "\n",
            " Want to try again? (yes/no)-yes\n",
            "\n",
            " Enter the Properties\n",
            "\n",
            "Flow rate Q(STB/D)- 200\n",
            "\n",
            "Oil viscocity(cp)- 100\n",
            "\n",
            "Permeability(mD)- 150\n",
            "\n",
            "Reservoir thickness(ft)- 30\n",
            "\n",
            " Want to try again? (yes/no)-n\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YpF1eDzIOYGV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# You can clearly see how increasing the viscocity of oil increased the pressure drop by a huge margin.\n",
        "#in easy words, thicker the oil, more pressure it requires to move, more pressure it looses on its journey to the well."
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UUUBW__5eH1S",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jUdO_-u3eLTb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dx4ccNnxeX-p",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}